Study population and setting
Authors used a stochastic model (i.e., one that takes randomness into account) stratified into 5-year age groups to estimate the effectiveness of non-pharmaceutical interventions (NPIs) in preventing new cases, hospitalizations, ICU bed demand, and deaths from COVID-19 in Wales, Scotland, and Northern Ireland. Over 66 million people aggregated to county-level administrative units were included in the model and a baseline R0 (basic reproductive number) of 2.7 was used. Interventions evaluated through the model were school closures, physical distancing, shielding of older persons, self-isolation of symptomatic persons, a combination of these four, and more locally-focused interventions, including a reduction in leisure events (e.g., spectator sports). Finally, authors estimated the impact increased childcare by grandparents would have on the effectiveness of these interventions, namely school closures.
Summary of Main Findings
In the absence of NPIs, the case-fatality rate was estimated to be 1.5% (95% PI 1.3-1.7), and the infection-fatality ratio was estimated to be 0.63% (95% PI 0.45-0.79); this was estimated to result in a peak number of required ICU beds of 200,000 and 350,000 total deaths. When implemented in the middle of the peak of the unmitigated epidemic, on average, each intervention delayed the peak by 3-8 weeks and decreased the total number of cases by 20-30%. Model results suggest that when implemented locally, the effect of school closures, physical distancing, shielding of older persons, and self-isolation of symptomatic cases only modestly reduced the total number of cases and deaths compared to implementing them nationally. Suspending leisure activities such as spectator sports by 75% averted 1.9 million cases. Model results indicate that over a 3-month time period, the beneficial effects of school closures would be virtually eliminated in terms of the number of deaths and peak ICU bed needs due to the increased contact per weekday between children younger than 15 years and older persons (i.e., grandparents).
The model estimated both case-fatality and infection-fatality ratios, which allowed it to account for asymptomatic and undiagnosed infections in addition to symptomatic cases. Authors also ran simulations using a distribution of R0 values, SARS-CoV-2 introduction dates, and timing of intervention implementation, which provided robust uncertainty bounds for the model projections. The modeling framework (i.e., location-based contact matrices) makes the scenarios well-oriented for policy making.
Projections of the relative effect of the NPIs considered in this study are estimates only and derived from measurements taken in 2006. Per contact matrix (home, work, school, other) and intervention combination (e.g., home contacts assuming school closures), authors assumed decreases in contacts would be uniform between each five year age group pairing. However, the model did not structure individuals by household, which limits the ability to evaluate the impact of these interventions on household contacts. Challenges in comparing the results from this study to empirical UK data exist since implemented interventions differ from the scenarios evaluated here.
Going beyond the growing body of evidence estimating effectiveness of non-pharmaceutical interventions (NPIs) for individual countries, this study evaluated the impact of NPIs on different spatial scales, and compared their effectiveness when implemented at the local versus national level. This study also considered how the impact of certain NPIs could be negated by resulting changes to contact patterns, such as grandparents being responsible for childcare during school closures.
This review was posted on: 21 July 2020